DANIEL CARLSON

SUMMARY

• PhD student with research experience optimizing hybrid memory systems.
• Recipient of several academic awards, including being recognized as an FIU College of Engineering and Computing Outstanding Graduate.
• Experience in Python, Java, C, web development, and more.

EDUCATION

• Researching optimization of hybrid memory systems.
• Planning to research applications of machine learning within systems.

• Graduated from the Honors College, 4.0 GPA
• Member of Upsilon Pi Epsilon
• Member of Google Developer Student Clubs

• Valedictorian, 4.0 GPA

AWARDS, SCHOLARSHIPS, & HONORS

• 2022, FIU College of Engineering and Computing Outstanding Graduate
• 2022, Nominated by KFSCIS for CRA's Outstanding Undergraduate Student Award 2023
• 2020, Honors College Dean's Engagement Award
• 2019 - 2022, 9x Dean's List Honoree
• 2019, National Merit Scholarship

RESEARCH EXPERIENCE

• Researched strategies for efficient memory management on tiered memory systems.
• Designed data visualizations that lead to a better understanding of performance.
• Collaborated with Ph.D. researchers to publish findings with a manuscript “Allocation Policies Matter for Hybrid Memory Systems” under review at USENIX ATC’23.

PUBLICATIONS

• Adnan Maruf, Ashikee Ghosh, Daniel Carlson, Janki Bhimani, Raju Rangaswami. Allocation Policies Matter for Hybrid Memory Systems, 2023 USENIX Annual Technical Conference. (Ongoing)

PROJECTS

Researched to invent new allocation policies for optimizing hybrid memory systems with emerging byte addressable persistent memories (Intel Optane DC PMM). Designed visualization tools to present analysis of the data collected. Deployed and ran experiments on customized CentOS kernel to gather performance.

Developed an Apple Watch and iOS application that communicates via Bluetooth with hardware in a user's shoes to monitor and display a user's weight. Led documentation and repository management using GitHub.

Developed a front-end JavaScript library that can efficiently generate smooth heat maps from discrete 2D arrays on the client machine.

RELEVANT COURSEWORK

Algorithm Techniques, Computational Geometry, Computer Architecture, Data Structures, Database Management, Human Computer Interaction, Logic for Computer Science, Natural Language Processing, Operating Systems, Parallel Computing, Programming Languages, Software Engineering, Systems Programming, and UNIX Programming.

RELEVANT SKILLS